Simulation And Technological Optimization Of The Micro-machining Of Graphene Reinforced Aeronautical Metal Matrix Composites

Nanoparticle reinforced metal matrix nanocomposites(MMNCs)have been widely used in aerospace fields.With the application of graphene,graphene(Gr)has become an attractive reinforcement to metal matrix nanocomposites(MMNCs)owing to its excellent mechanical and physical properties.To investigate the machinability of the new nanocomposites,a two-dimension finite element(FE)model of orthogonal micromachining of Gr-MMNCs was first established in this paper.Machining of Gr-MMNCs is a complex dynamic process of high strain,high strain rate and high temperature,including a series of complicated phenomena such as highly nonlinear plastic deformation and fracture failure.To simulate the complex dynamic machining of Gr-MMNCs,a complete FE model was proposed with the consideration of the constitutive models,failure models,friction models and mesh generation technique.In FE modeling,a random distribution algorithm of graphene nanoplatelets(GNPs)has been developed to simulate the both random distributions of the position and orientation of GNPs practically.And a second development program was introduced into the model on the basis of the Python language in ABAQUS to realize the automatic generation of two-dimension FE model.After experimental validation of the micromechanical FE model,the effects of various technological parameters on the average cutting force were investigated by using the results of FE simulation.Then,the influences of the group of parameters on cutting force were quantitatively analyzed for comparison by the method of factor analysis based on mathematical statistics software.It was found that the most significant parameter in the micro-machining process of Gr-MMNCs is the depth of cut,and the average size and weight fraction of graphene are the following significant ones.Based on the results of factor analysis,the strategy of process optimization was obtained.Meanwhile,an empirical model of the average cutting force related with these significant parameters was also obtained for the prediction of the cutting force of Gr-MMNCs.